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On-board SPECT for localizing functional targets: A simulation study

MEDICAL PHYSICS 2009年第5期36卷 1727-1735页

作者： Roper, Justin Bowsher, James Yin, Fang-Fang Duke Univ Med Ctr Dept Radiat Oncol Med Phys Grad Program Durham NC 27710 USA

Single photon emission computed tomography (SPECT) was investigated for imaging on-board radiation therapy machines in order to localize functional and molecular targets. A computer-simulated female NCAT phantom was positioned supine on a flat-top treatment couch. Twenty tumor locations were defined in the upper torso. The eight lung tumors were subject to the effects of respiratory motion. Tumor diameters of 10.8, 14.4, and 21.6 mm were simulated for tumor-to-background ratios of 3:1 and 6:1 that are characteristic of the radiotracer (99m)Tc-sestamibi. Projection images representing scan times of 4, 8, and 20 min were simulated for an anterior, half-circular trajectory. Images were reconstructed with attenuation correction by ordered-subsets expectation maximization (OSEM) using six subsets and five iterations. Contrast-to-noise ratios (CNRs) were calculated from ensembles of 25 images. Cross correlation with a noise-free tumor template was used to select the most suspicious tumor location within a 14.4-mm-radius search volume surrounding each tumor, with only that one tumor in each search volume. Localization accuracy was assessed by calculating average distances between measured and true tumor locations. Localization accuracy and CNRs were strongly affected by tumor location relative to the detector trajectory. For example, CNR values near the chest wall were greater by a factor of 3.5 than for tumors near the spine and posterior ribs, a much greater effect than the factor of 1.6 difference in CNR between 6:1 and 3:1 tumor uptakes. Typically, tumors of 6:1 uptake were localized as accurately with 4 min of scan time as tumors of 3:1 uptake that had been imaged for 20 min. Using 4 min scans, 14.4 and 21.6 mm anterior tumors of 6:1 uptake were localized within 2 mm. These results suggest that SPECT, on-board radiation therapy machines, may be a viable modality for localizing certain functional and molecular targets using relatively short scan times.

关键词： expectation-maximisation algorithm image reconstruction lung medical image processing object detection phantoms radiation therapy single photon emission computed tomography tumours

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Penalized factor mixture analysis for variable selection in clustered data

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第12期53卷 4301-4310页

作者： Galimberti, Giuliano Montanari, Angela Viroli, Cinzia Univ Bologna Dipartimento Sci Stat I-40126 Bologna Italy

A model-based clustering approach which contextually performs dimension reduction and variable selection is presented. Dimension reduction is achieved by assuming that the data have been generated by a linear factor model with latent variables modeled as Gaussian mixtures. Variable selection is performed by shrinking the factor loadings though a penalized likelihood method with an L1 penalty. A maximum likelihood estimation procedure via the EM algorithm is developed and a modified BIC criterion to select the penalization parameter is illustrated. The effectiveness of the proposed model is explored in a Monte Carlo simulation study and in a real example. (C) 2009 Elsevier B.V. All rights reserved.

关键词： MODEL ANALYZERS Analysers LU1 expectation-maximisation algorithm Monte Carlo technique maximum likelihood estimation Input variables

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On some lifetime distributions with decreasing failure rate

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第12期53卷 4433-4440页

作者： Chahkandi, M. Ganjali, M. Shahid Beheshti Univ Dept Stat Tehran Iran

A new two-parameter distribution family with decreasing failure rate arising by mixing power-series distribution and exponential distribution is introduced. This family includes some well-used mixing distributions. Various properties of this family are discussed and the estimation of parameters are obtained by method of maximum likelihood. An EM algorithm is proposed for computing the estimates and expression for their asymptotic variances and covariances are derived. Simulation studies are performed and experimental results are illustrated based on real data sets. (C) 2009 Elsevier B.V. All rights reserved.

关键词： MONOTONE HAZARD RATE MAXIMUM-LIKELIHOOD ESTIMATION EXPONENTIAL-DISTRIBUTIONS EM algorithm WEIBULL DISTRIBUTION GAMMA-DISTRIBUTION CENSORED-DATA MIXTURE PARAMETERS BOUNDS censored data mixtures observational data Blending expectation-maximisation algorithm maximum likelihood Exponential distribution Parameter estimation Weibull distribution maximum likelihood estimation decreasing failure rate family

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Complexity control in a mixture model by the Hardy-Weinberg equilibrium

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第5期53卷 1711-1719页

作者： Bingham, Ella Mannila, Heikki Univ Helsinki Helsinki Inst Informat Technol FIN-00014 Helsinki Finland Aalto Univ Helsinki Inst Informat Technol FIN-02015 Espoo Finland

A method of complexity control in multinomial mixture modeling of multiple-marker genotype data, imposing the Hardy-Weinberg equilibrium (HWE) between the genotype values, is studied. This is a very natural restriction, and known to hold at population level under modest assumptions. The hypothesis under study is that imposing this restriction will prevent overfitting and lead to a better model. This is shown to indeed be case. Experimental results an chromosomes 1 and 17 of the HapMap data demonstrate that the restricted model generalizes better to unseen data, and also finds clusters that correspond better to the ethnic groups of the HapMap, when compared with a model without the HWE restriction. (C) 2008 Elsevier B.V. All rights reserved.

关键词： MULTILOCUS GENOTYPE DATA POPULATION-STRUCTURE MAXIMUM-LIKELIHOOD BAYESIAN-ANALYSIS EM algorithm ADMIXTURE PROPORTIONS INFERENCE MARKERS GENOME Genome Complexity HapMap expectation-maximisation algorithm maximum likelihood Restriction Bayes methods Mixture models Population structure

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On estimation and influence diagnostics for the Grubbs' model under heavy-tailed distributions

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第4期53卷 1249-1263页

作者： Osorio, Felipe Paula, Gilberto A. Galea, Manuel Univ Valparaiso CIMFAV Dept Estadist Valparaiso 5030 Chile Univ Sao Paulo Inst Matemat & Estatist BR-05508 Sao Paulo Brazil

The Grubbs' measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

关键词： LINEAR STRUCTURAL RELATIONSHIPS COMPARATIVE CALIBRATION MODELS MIXED-EFFECTS MODELS LOCAL INFLUENCE INCOMPLETE-DATA MAXIMUM-LIKELIHOOD MEASURING DEVICES SCALE MIXTURES T-DISTRIBUTION EM algorithm Diagnosis Thermocouple maximum likelihood expectation-maximisation algorithm measuring instruments Parameter estimation Student's t-distribution Gaussian distribution outliers Robustness

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Three-dimensional channel modelling using spherical statistics for multiple-input multiple-output systems

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IET COMMUNICATIONS 2009年第1期3卷 48-56页

作者： Mammasis, K. Stewart, R. W. Pfann, E. Freeland, G. Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Steepest Ascent Ltd Glasgow G4 0UW Lanark Scotland

Recently, the third generation partnership standards bodies (3GPP/3GPP2) have defined a two-dimensional channel model for multiple-input multiple-output (MIMO) systems, where the propagating plane waves are assumed to arrive only from the azimuthal direction and therefore not include the elevation domain. As a result of this assumption, the derived angle-of-arrival (AoA) distribution is characterised only by the azimuth direction of these waves. The AoA distribution of multipaths is implemented with a novel three-dimensional approach. The von Mises-Fisher (VMF) probability density function is used to describe their distribution within the propagation environment in both azimuth and co-latitude. More specifically, the proposed model uses a mixture of VMF distributions. A mixture can be composed of any number of clusters and this is clutter specific. The parameters of the individual cluster of scatterers within the mixture are derived and an estimation of those parameters is achieved using the spherical K-means algorithm and also the expectation maximisation algorithm. Statistical tests are provided to measure the goodness of fit of the proposed model. The results indicate that the proposed model fits well with MIMO experimental data obtained from a measurement campaign in Germany.

关键词： channel model Scattering expectation-maximisation algorithm Plane waves Sphericity azimuth output system goodness of fit multiple input multiple output systems

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Population pharmacokinetic/pharmacodynamic mixture models via maximum a posteriori estimation

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第12期53卷 3907-3915页

作者： Wang, Xiaoning Schumitzky, Alan D'Argenio, David Z. Univ So Calif Dept Biomed Engn Los Angeles CA 90089 USA Univ So Calif Dept Math Los Angeles CA 90089 USA Bristol Myers Squibb Co Clin Discovery Strateg Modeling & Simulat Grp Princeton NJ 08543 USA

Pharmacokinetic/pharmacodynamic phenotypes are identified using nonlinear random effect models with finite mixture structures. A maximum a posteriori probability estimation approach is presented using an EM algorithm with importance sampling. Parameters for the conjugate prior densities can be based on prior studies or set to represent vague knowledge about the model parameters. A detailed simulation study illustrates the feasibility of the approach and evaluates its performance, including selecting the number of mixture components and proper subject classification. (C) 2009 Elsevier B.V. All rights reserved.

关键词： EM algorithm BAYESIAN-APPROACH LIKELIHOOD expectation-maximisation algorithm Conjugate prior model parameters Bayes methods random effect Maximum a posteriori estimation importance sampling

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An expert system for predicting nonlinear aeroelastic behavior of an airfoil

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JOURNAL OF SOUND AND VIBRATION 2009年第3-5期319卷 1312-1329页

作者： Popescu, C. A. Wong, Y. S. Lee, B. H. K. Grant MacEwan Coll Dept Math & Stat Edmonton AB T5J 4S2 Canada Univ Alberta Dept Math & Stat Sci Edmonton AB T6G 2G1 Canada Inst Aerosp Res Ottawa ON K1A 0R6 Canada

In this paper we present an expert system to perform steady-state response predictions. We consider an aeroelastic model simulating a two degree-of-freedom airfoil oscillating in pitch and plunge with a freeplay nonlinearity in the pitch degree-of-freedom. In the proposed data-driven methodology, a freeplay is first confirmed, and then the locations of the switching points are determined. A state-space formulation is constructed to model the piece-wise linear system. The parameters of the system are estimated using the Kalman filter and the expectation maximization algorithm. The attractive feature of the present approach is its ability to accurately predict the steady-state behavior of the nonlinear aeroelastic system with freeplay, using only a limited amount of transient input data. To demonstrate the effectiveness of the proposed methodology, we present applications to freeplay aeroelastic data arising from wind tunnel experiments and numerical simulations. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： EM algorithm expectation-maximisation algorithm Airfoils Aeroelastics Expert System plunge pitch Kalman filters nonlinearity

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Quantitative simultaneous ^99mTc/¹²³I cardiac SPECT using MC-JOSEM

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MEDICAL PHYSICS 2009年第2期36卷 602-611页

作者： Ouyang, Jinsong Zhu, Xuping Trott, Cathryn M. El Fakhri, Georges Massachusetts Gen Hosp Div Nucl Med & Mol Imaging Boston MA 02114 USA Harvard Univ Sch Med Dept Radiol Boston MA 02115 USA

Simultaneous rest Tc-99m-Sestamibi/I-123-BMIPP cardiac SPECT imaging has the potential to replace current clinical Tc-99m-Sestamibi rest/stress imaging and therefore has great potential in the case of patients with chest pain presenting to the emergency department. Separation of images of these two radionuclides is difficult, however, because their emission energies are close. The authors previously developed a fast Monte Carlo (MC)-based joint ordered-subset expectation maximization (JOSEM) iterative reconstruction algorithm (MC-JOSEM), which simultaneously compensates for scatter and cross talk as well as detector response within the reconstruction algorithm. In this work, the authors evaluated the performance of MC-JOSEM in a realistic population of Tc-99m/I-123 studies using cardiac phantom data on a Siemens *** system using a standard cardiac protocol. The authors also compared the performance of MC-JOSEM for estimation tasks to that of two other methods: standard OSEM using photopeak energy windows without scatter correction (NSC-OSEM) and standard OSEM using a Compton-scatter energy window for scatter correction (SC-OSEM). For each radionuclide the authors separately acquired high-count projections of radioactivity in the myocardium wall, liver, and soft tissue background compartments of a water-filled torso phantom, and they generated synthetic projections of various dual-radionuclide activity distributions. Images of different combinations of myocardium wall/background activity concentration ratios for each radionuclide were reconstructed by NSC-OSEM, SC-OSEM, and MC-JOSEM. For activity estimation in the myocardium wall, MC-JOSEM always produced the best relative bias and relative standard deviation compared with NSC-OSEM and SC-OSEM for all the activity combinations. On average, the relative biases after 100 iterations were 8.1% for Tc-99m and 3.7% for I-123 with MC-JOSEM, 39.4% for Tc-99m and 23.7% for I-123 with NSC-OSEM, and 20.9% for Tc-99m with SC-O

关键词： cardiology expectation-maximisation algorithm image reconstruction iodine compounds iterative methods medical image processing Monte Carlo methods muscle organic compounds phantoms single photon emission computed tomography technetium compounds

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A latent variable regression model for capture-recapture data

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第7期53卷 2740-2746页

作者： Thandrayen, Joanne Wang, Yan Univ S Australia Sch Math & Stat Adelaide SA 5000 Australia RMIT Univ Sch Math & Geospatial Sci Melbourne Vic 3000 Australia

Capture-recapture methods are used to estimate the prevalence of diseases in the field of epidemiology. The information used for estimation purposes are available from multiple lists, whereby giving rise to the problems of list dependence and heterogeneity. In this paper, modelling is focused on the heterogeneity part. We present a new binomial latent class model which takes into account both the observed and unobserved heterogeneity within capture-recapture data. We adopt the conditional likelihood approach and perform estimation via the EM algorithm. We also derive the mathematical expressions for the computation of the standard error of the unknown population size. An application to data on diabetes patients in a town in northern Italy is discussed. (c) 2009 Elsevier B.V. All rights reserved.

关键词： Standard error Built environment population size expectation-maximisation algorithm maladjustment Mathematical Formulas Binomial

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